We are improving CT colonography (virtual colonoscopy) by developing computer-assisted diagnosis methods. These methods attempt to identify and characterize colonic polyps automatically, thereby increasing physician accuracy and efficiency and helping patients by finding their polyps. We made a number of advances over the past year, including advances in colon and polyp segmentation, feature extraction methods, false positive reduction and classifier optimization. We improved our innovative technique to use the tenia coli (longitudinal muscle bands) as a guide for orienting the supine and prone virtual colonoscopies. This technique has broad implications for research and clinical image interpretation. We developed a method to help co-register virtual colonoscopies and optical colonoscopies of the same patient using a technique called the "normalized distance along the colon centerline". We found an explanation for the observed low sensitivity for detecting hyperplastic polyps compared to adenomatous polyps on virtual colonoscopy. Hyperplastic polyps tend to be flatter than adenomatous polyps, rendering them less conspicuous to radiologists. This is beneficial to patients because hyperplastic polyps have much lower malignant potential than adenomatous polyps and detecting hyperplastic polyps could lead to unnecessary polypectomy. We licensed our CAD software to a company that is in the process of commercializing the software. We anticipate our research being able to help patients directly in the near future when this commercialization is successful and the technology moves from the "bench-to-the-bedside".